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Bridging the gap between energy-to-GDP ratio and composite energy intensity index

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  • Ang, B.W.
  • Goh, Tian

Abstract

The energy-to-GDP ratio (EGR) is an indicator often used as a proxy for economy-wide energy efficiency in policy formulation and analysis. It is easy to compute and interpret, but its limitations as an energy efficiency indicator are also well known. Another widely used indicator is the composite energy intensity (CEI) index constructed from disaggregated energy and activity data. The CEI index is seen as a better proxy for energy efficiency but it is more difficult to construct as compared to the EGR. Countries have computed and compared the two indexes and reported their divergence in capturing energy efficiency trends. While economic structure change is one explanation for the divergence, it is not the only contributing factor and the issue has not been studied in detail. This study seeks to fill the gap. It dissects and discusses the fundamentals of the two indicators, and establishes a formal linkage between them by introducing a factor termed the “activity correction” (AC) effect. A case study is presented. The significance and policy implications of the AC effect are discussed.

Suggested Citation

  • Ang, B.W. & Goh, Tian, 2018. "Bridging the gap between energy-to-GDP ratio and composite energy intensity index," Energy Policy, Elsevier, vol. 119(C), pages 105-112.
    • Handle: RePEc:eee:enepol:v:119:y:2018:i:c:p:105-112
    DOI: 10.1016/j.enpol.2018.04.038
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    4. Alexander N. Semin & Vadim V. Ponkratov & Kirill G. Levchenko & Andrey S. Pozdnyaev & Nikolay V. Kuznetsov & Olga V. Lenkova, 2019. "Optimization Model for the Russian Electric Power Generation Structure to Reduce Energy Intensity of the Economy," International Journal of Energy Economics and Policy, Econjournals, vol. 9(3), pages 379-387.
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    9. Trotta, Gianluca, 2020. "Assessing energy efficiency improvements and related energy security and climate benefits in Finland: An ex post multi-sectoral decomposition analysis," Energy Economics, Elsevier, vol. 86(C).
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    14. Goh, Tian & Ang, B.W., 2020. "Four reasons why there is so much confusion about energy efficiency," Energy Policy, Elsevier, vol. 146(C).
    15. Cheng, Shulei & Fan, Wei & Chen, Jiandong & Meng, Fanxin & Liu, Gengyuan & Song, Malin & Yang, Zhifeng, 2020. "The impact of fiscal decentralization on CO2 emissions in China," Energy, Elsevier, vol. 192(C).
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    19. Livas-García, A. & Bonilla, D. & Escalante Soberanis, M.A. & Bassam, A., 2019. "Projecting the energy pathway using a methodological sequence: The case of Mexico," Energy Policy, Elsevier, vol. 135(C).
    20. Su, Bin & Goh, Tian & Ang, B.W. & Ng, Tsan Sheng, 2022. "Energy consumption and energy efficiency trends in Singapore: The case of a meticulously planned city," Energy Policy, Elsevier, vol. 161(C).
    21. Yang, Xue & Xu, He & Su, Bin, 2022. "Factor decomposition for global and national aggregate energy intensity change during 2000–2014," Energy, Elsevier, vol. 254(PB).
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    23. Nie, Yonghui & Qiu, Yu & Yang, Annan & Zhao, Yan, 2024. "Risk-limiting dispatching strategy considering demand response in multi-energy microgrids," Applied Energy, Elsevier, vol. 353(PA).

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